Jobs at Techdome

Leads the architecture and delivery of enterprise ServiceNow implementations across multiple modules. Designs scalable platform solutions, integrations, CMDB and CSDM strategies, governance standards, upgrade plans, and performance improvements. Facilitates client workshops, translates requirements into technical designs, reviews development work, supports estimations and presales, and guides best-practice implementation. Requires deep ServiceNow, ITSM, scripting, integration, and client-facing expertise.

Build and deploy production-grade machine learning, deep learning, and Generative AI solutions. Responsibilities include developing models, RAG pipelines, AI agents, prompt engineering, data and training pipelines, scalable APIs, and MLOps practices. The role evaluates and optimizes model performance, cost, and latency while collaborating with product, data, and engineering teams to move AI capabilities from proof of concept to production.

Build and own end-to-end web applications, including responsive frontends, scalable backend services, APIs, database integrations, authentication, and payment systems. Deploy cloud-native applications using Docker and CI/CD pipelines, write clean and testable code, participate in Agile ceremonies and code reviews, and mentor junior developers. The role requires strong JavaScript or TypeScript skills, React or Angular, Node.js, SQL and NoSQL databases, REST APIs, microservices, Git, and cloud services.

Develop and maintain enterprise Sitecore websites and digital experiences across Sitecore XP/XM and XM Cloud. Build headless components with Sitecore JSS, Next.js, or React; develop C# and .NET backend features; configure content, workflows, personalization, and multisite environments; integrate CRM, search, and third-party systems; support migrations, performance optimization, security, and agile collaboration.

Design, develop, configure, and integrate scalable Salesforce solutions for enterprise clients. Responsibilities include Apex, LWC, Visualforce, Flows, Salesforce cloud implementations, external-system integrations, data modeling, CI/CD deployments, testing, performance and security best practices, troubleshooting, user support, and mentoring junior developers.

Build and manage secure, highly available cloud infrastructure and CI/CD pipelines. Responsibilities include Infrastructure as Code, Kubernetes and container management, monitoring, logging, security, access control, disaster recovery, cost optimization, and production troubleshooting. The role requires strong cloud, Terraform, Kubernetes, Docker, Linux, networking, scripting, and pipeline experience, with participation in on-call support.

Designs and owns scalable enterprise data platforms across ingestion, storage, processing, serving, and analytics. Responsibilities include cloud data lake, lakehouse, and warehouse architecture; data modeling; governance, security, quality, metadata, and lineage standards; architecture reviews; technology selection; cost optimization; team guidance; stakeholder collaboration; and presales support. Requires strong Snowflake or Databricks, cloud, SQL, data modeling, programming, Spark, and ETL/ELT expertise.

Build and optimize batch and real-time ETL/ELT pipelines using Python, PySpark, SQL, Snowflake, Databricks, and cloud platforms. Develop transformation and orchestration layers, implement data quality monitoring and alerting, optimize performance and cloud costs, and collaborate with architects, analysts, and data scientists. The role also requires data warehousing, dimensional modeling, CI/CD, version control, and documentation practices.

Design, develop, and maintain scalable Python backend applications, RESTful and GraphQL APIs, database systems, integrations, and asynchronous services. Deploy cloud-based services using Docker and CI/CD pipelines, write automated tests, participate in code reviews, contribute to technical architecture, and mentor junior developers. The role requires expertise in Python frameworks, SQL and NoSQL databases, authentication, cloud platforms, distributed systems, and asynchronous programming.

Own end-to-end architecture for high-scale healthcare, fintech, AI, and SaaS products. Design secure, reliable, cloud-native systems; make decisions on APIs, data models, distributed architecture, observability, scalability, and cost. Write production code, resolve performance and availability issues, establish engineering standards, conduct design and code reviews, and mentor senior engineers. The role requires operating systems serving more than 100,000 users and hands-on experience with Node.js, React, cloud platforms, and security-critical domains.

Supports corporate and commercial legal matters, including drafting and reviewing contracts, Companies Act compliance, board documentation, ROC filings, contract tracking, employment documents, due diligence, legal research, and coordination with external counsel and company secretaries.

Designs enterprise data architectures, models, integration solutions, pipelines, and governance standards for supply chain and manufacturing environments. Leads Azure and Databricks data platform implementations, including Azure Data Factory, Synapse Analytics, and Data Lake solutions. Collaborates with stakeholders, engineers, and business teams to translate requirements into scalable architectures, improve data quality, support modernization, and optimize enterprise data flows.

Supports People Operations across onboarding, employee exits, records, attendance, leave, payroll inputs, statutory compliance, HR documentation, engagement events, employee queries, and basic reporting. The intern will use Keka HRMS, spreadsheets, and AI tools while learning HR operations in a fast-growing technology company.

Own the end-to-end architecture of a multi-tenant AI platform, including workflow, agent runtime, semantic, integration, and data layers. Define architecture decisions, APIs, event schemas, security standards, tenancy models, and scalability requirements. Collaborate with AI engineers, enterprise customers, and security teams while reviewing designs and critical code. Ensure reliability, tenant isolation, disaster recovery, data retention, and support for up to 10,000 concurrent runs.

Evaluates AI-generated quantitative research and systematic fixed-income trading strategies. Reviews backtesting methodologies, yield curve models, carry and roll-down analytics, relative-value strategies, statistical rigor, transaction costs, liquidity assumptions, and implementation accuracy. Identifies flaws such as lookahead bias, overfitting, and data snooping, then provides actionable written feedback. Requires extensive quantitative finance expertise, rates-market knowledge, and proficiency in Python or R.

Performs end-to-end QA and functional testing within the SOFICO Miles platform. Designs and executes test cases, coordinates User Acceptance Testing, investigates defects, translates business requirements into validation scenarios, guides testers, and improves testing methodologies while collaborating with business and technical stakeholders.

Owns finance operations across India, US, and UAE entities, including monthly close, payroll, banking, tax and corporate compliance, receivables, cash-flow forecasting, entity-level reporting, and auditor coordination. The role also leads finance-process automation using n8n and AI tools while partnering directly with company founders.

QA Intern will develop UI automation, API testing, and performance/load testing skills while working on real products with mentorship. Responsibilities include writing automated tests using Playwright or Selenium, applying programming fundamentals, using AI tools such as Claude responsibly, solving problems, and communicating clearly. Exposure to Postman, REST, performance testing, GitHub portfolios, or testing and development projects is beneficial. Successful interns may advance to a full-time SDET role.

Translates business needs into clear, testable requirements for AI and data products. Leads discovery workshops, process mapping, backlog refinement, business-rule definition, configuration sessions, and traceability from requirements through testing. Supports UAT, AI-output validation, defect triage, stakeholder sign-off, change control, and documentation. Requires strong requirements elicitation, process modeling, Agile delivery, SQL and data literacy, AI acceptance-criteria definition, communication, and workshop facilitation.

Build and maintain data foundations for AI agents, analytics, scorecards, and dashboards. Responsibilities include developing ingestion pipelines and enterprise connectors, modeling raw-to-mart layers, managing metadata and vector indexes, implementing data quality and lineage controls, and supporting governed data stores. The role also covers API integrations, incremental ingestion, security controls, testing, release activities, and data validation. Preferred experience includes RAG preparation, unstructured content processing, knowledge graphs, LLM applications, and regulated life sciences data.